Classification of Data

 

Data can be anything —text, numbers, images, files, audio, video—virtually any form of digital

information.

 

For an organization to function effectively and make informed decisions, classifying data is crucial .

It helps in managing, securing, and leveraging data appropriately across systems.

 

Why Does Data Classification Matter?

Proper classification allows organizations to:

Choose the right storage solution

Use the appropriate processing tools

Identify and handle sensitive or regulated data

Ensure compliance (e.g., with GDPR, HIPAA)

Enhance data security

Implement access controls

Optimize system performance

Reduce operational costs

 

Data comes in many forms, and knowing the differences helps determine how it should be stored, processed, and analyzed.

 

When designing a data architecture for storing, processing and analyzing.

Several critical questions arise:

What kind of data is it?

Is it structured , semi-structured , or unstructured ?

Is the data sensitive ?

How will it be processed and accessed ?

To answer these questions accurately and build an efficient data strategy, data classification is key .

 

Common Ways to Classify Data

While there’s no single "correct" way to classify data, the following categories are widely used:

By Structure – Based on how data is organized (e.g., structured, semi-structured, unstructured)

By Source – Based on who or what generated the data (e.g., human-generated, machine-generated)

By Sensitivity – Based on how critical or private the data is (e.g., personal data, confidential records)

 

You can also define custom classifications based on your organization's goals or industry needs—for example, real-time vs. historical data, or internal vs. external data.